AI is no longer knocking on the door. It’s in the room, sitting at the table and quietly rewriting how work gets done. For leaders, the question is no longer should we use AI — it’s how do we lead well when we do?

Let’s be clear: AI changes the how, but not the why. High performance still relies on the same fundamentals — clarity, feedback, coaching, recognition. But in a world where machines are handling more of the repeatable tasks, we have to rethink how we define roles, measure contribution and grow capability.

Here are five shifts that great leaders are making to manage performance in the age of AI.

1. Stop managing tasks, start managing clarity

When AI is involved in delivering outcomes, the old performance model starts to creak. Who’s accountable when things go wrong — the person, or the tool?

Take a start-up that automated customer onboarding. It worked, mostly. But when errors crept in, no one was sure who was responsible. That’s not a performance problem — it’s a leadership one. Because clarity is a leadership choice.

Great leaders now ask:

• What are people still actually responsible for?
• Where does AI support, and where does it lead?
• What does ownership look like when machines are in the mix?

If your team doesn’t know how their role fits in a blended workforce, don’t be surprised when performance dips.

2. Redefine roles, don’t just rewrite job descriptions

It’s tempting to update job specs and call it done. But that won’t cut it. AI is shifting not just what people do, but how they think about their value.

If a tool suggests next steps in a workflow, is the person expected to question it, or follow it? If the AI gets it wrong, whose judgement counts?

The leaders getting this right are explicit. They draw a clear line between:

• What AI owns, and what it doesn’t
• Where human judgement overrides automation
• How people are expected to engage with the tools they’ve been given

And here’s the truth, they treat AI like a colleague. Accountable. Fallible. Open to challenge. Because that’s the only way to build a culture where performance still matters.

3. Measure what really matters

If AI drafts the presentation, edits the photo or writes the code. W

hat are you actually evaluating when you review someone’s performance?

The human edge is now in:

• Framing the right question
• Adding context and nuance
• Spotting what doesn’t quite feel right

But most performance systems still measure output — volume, speed, efficiency. Leaders need to evolve those metrics. Fast.

Instead of asking how much did you do, ask:

• How well did you brief the AI?
• How did you shape the outcome?
• How did your judgement improve the result?

Good leadership means knowing what good looks like — even when machines are helping to deliver it.

4. Coach for judgement, not just skill

When AI does more of the doing, your job as a leader is to help people think better. Coaching becomes less about process, and more about sharpening human insight.

One leader noticed their sales team becoming passive after introducing an AI assistant. So they changed the coaching focus:

• Ask better questions
• Know when to trust the tool, and when to override it
• Be confident enough to lead, not follow

The lesson? AI is a tool. Coaching is where you make sure people still use their brain.

5. Lead with values, not just tech

Performance doesn’t happen in a vacuum. It’s built on trust, purpose and culture. And culture is your job.

When AI shows up, fear often follows — fear of job loss, of irrelevance, of being replaced. The worst thing leaders can do is offer vague reassurance.

The best ones lead with values:

• We use AI transparently
• We prioritise ethical judgement
• We value collaboration and communication just as much as technical output

Performance reviews reflect that. They include:

• Ethical decision-making
• Communication about AI use
• Human-centred leadership in tech-enabled work

AI can optimise tasks. But only humans can build trust. And in the long run, that’s what sustains performance.

One final thought

The leaders who thrive in the age of AI won’t be the ones who automate the fastest. They’ll be the ones who stay human, even when the tools are dazzling.

Because performance — real performance — is still a deeply human endeavour.